2020
EMNLP
EMNLP 2020
SynET: Synonym Expansion using Transitivity
Abstract
AbstractIn this paper, we study a new task of synonym expansion using transitivity, and propose a novel approach named SynET, which considers both the contexts of two given synonym pairs. It introduces an auxiliary task to reduce the impact of noisy sentences, and proposes a Multi-Perspective Entity Matching Network to match entities from multiple perspectives. Extensive experiments on a real-world dataset show the effectiveness of our approach.
🌉
Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
Authors
Topics
Artificial Intelligence > Core AI > Interpretability
Artificial Intelligence > Learning Paradigms > Transfer Learning
Machine Learning > Core Methods > Representation Learning
Natural Language Processing > Applications > Information Extraction
Artificial Intelligence > Core AI > Knowledge Representation